The JAS-mine platform

Bringing real and simulated data together

With the aim to develop large-scale, data-driven models, the main
architectural choice of JAS-mine is to use whenever possible standard,
open-source tools already available in the software development
community.

The main value added of the platform are: (1)integration of I/O communication tools, in the form of embedded
RDBMS (relational database management systems) tools and automatic CSV table creation, (2) advanced multi-run tools to facilitate design of experiments (DOE), (3) sophisticated regression libraries that allow a complete separation of regression specifications from the code, and permit uncertainty analysis of the model outcome by bootstrapping the estimated coefficients across different simulation runs.

JAS-mine allows to separate data representation and management, which is
automatically taken care of by the simulation engine, from the
implementation of processes and behavioral algorithms, which should be
the primary concern of the modeler. This results in quicker, more robust
and more transparent model building.

A library implementing a number of different matching methods, to match different lists of agents

A library implementing a number of different alignment methods (including binary and multiple choice alignment), to force the microsimulation outcomes meeting some exogenous aggregate targets

A Regression library implementing a number of common econometric models, from
continuous response linear regression models to binomial and multinomial
logit and probit models, which includes automatic bootstrapping of the coefficients for uncertainty analysis of the model oucomes